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C. Braak (1983)
Principal Components Biplots and Alpha and Beta DiversityEcology, 64
W. Madow, T. Anderson (1959)
An Introduction to Multivariate Statistical Analysis
P. Robert, Y. Escoufier (1976)
A Unifying Tool for Linear Multivariate Statistical Methods: The RV‐CoefficientJournal of The Royal Statistical Society Series C-applied Statistics, 25
A. Wollenberg (1977)
Redundancy analysis an alternative for canonical correlation analysisPsychometrika, 42
C. O'Connor (1987)
An introduction to multivariate statistical analysis: 2nd edn. by T. W. Anderson. 675 pp. Wiley, New York (1984)
A. Israels (1984)
Redundancy analysis for qualitative variablesPsychometrika, 49
R. Payne, P. Lane, A. Ainsley, K. Bicknell, P. Digby, S. Harding, P. Leech, H. Simpson, A. Todd, P. Verrier, Rodger White, J. Gower, G. Wilson, L. Paterson (1987)
Genstat 5 Reference Manual
Agricultural Mathematics Group Box 100 6700 AC Wageningen The Netherlands
A. Rencher (1988)
On the use of correlations to interpret canonical functionsBiometrika, 75
Calyampudi Rao (1964)
The use and interpretation of principal component analysis in applied research
J. Gower (1989)
Multiple correspondence analysis and non-linear biplots.
(1984)
Multivariate observations. New York: Wiley
(1992)
Generalised biplots
C. Braak (1990)
Interpreting canonical correlation analysis through biplots of structure correlations and weightsPsychometrika, 55
T. Mathew, J. Carroll, P. Green, A. Chaturvedi (1979)
Mathematical Tools for Applied Multivariate Analysis
M. Tso (1981)
Reduced‐Rank Regression and Canonical AnalysisJournal of the royal statistical society series b-methodological, 43
Anderson Anderson (1951)
Estimating linear restrictions on regression coefficientsAnn. Math. Statist., 22
K. Gabriel, Charles Odoroff (1990)
Biplots in biomedical research.Statistics in medicine, 9 5
Nicky Hart (1986)
Inequalities in Health: The Individual Versus the Environment, 149
T. Anderson (1951)
Estimating Linear Restrictions on Regression Coefficients for Multivariate Normal DistributionsAnnals of Mathematical Statistics, 22
R. Velu (1991)
Reduced rank models with two sets of regressorsApplied statistics, 40
A. Izenman (1975)
Reduced-rank regression for the multivariate linear modelJournal of Multivariate Analysis, 5
B. Everitt, W. Krzanowski (2001)
Principles of Multivariate AnalysisTechnometrics, 43
M. Hill, R. Jongman, C. Braak, O. Tongeren (1987)
Data analysis in community and landscape ecologyJournal of Animal Science
D. Arenaza (2021)
Multivariate AnalysisEncyclopedic Dictionary of Archaeology
A. Höskuldsson (1988)
PLS regression methodsJournal of Chemometrics, 2
R. Clarke, M. Greenacre (1985)
Theory and Applications of Correspondence AnalysisJournal of Animal Ecology, 54
D. Bradu, K. Gabriel (1978)
The Biplot as a Diagnostic Tool for Models of Two-Way TablesTechnometrics, 20
C. Eckart, G. Young (1936)
The approximation of one matrix by another of lower rankPsychometrika, 1
A. Aastveit, H. Martens (1986)
ANOVA Interactions Interpreted by Partial Least Squares RegressionBiometrics, 42
(1989)
Generalized linear models (second edition)
R. Velu, G. Reinsel, D. Wichern (1986)
Reduced rank models for multiple time seriesBiometrika, 73
E. Burg, J. Leeuw (1990)
Nonlinear redundancy analysisBritish Journal of Mathematical and Statistical Psychology, 43
K. Gabriel (1971)
The biplot graphic display of matrices with application to principal component analysisBiometrika, 58
A. Kunst, C. Looman, J. Mackenbach (1990)
Socio-economic mortality differences in The Netherlands in 1950-1984: a regional study of cause-specific mortality.Social science & medicine, 31 2
C. Braak (1990)
Interpreting Canonical Correlation Analysis through Biplots of Structure Correlations and Weights
C. Braak (1988)
CANOCO - a FORTRAN program for canonical community ordination by [partial] [etrended] [canonical] correspondence analysis, principal components analysis and redundancy analysis (version 2.1)
P. Davies, M. Tso (1982)
Procedures for Reduced‐Rank RegressionApplied statistics, 31
L. Lefkovitch (1986)
Linear Predictivity: An Alternative for MANOVA and Multivariate Multiple RegressionBiometrical Journal, 28
Regression problems with a number of related response variables are typically analyzed by separate multiple regressions. This paper shows how these regressions can be visualized jointly in a biplot based on reduced‐rank regression. Reduced‐rank regression combines multiple regression and principal components analysis and can therefore be carried out with standard statistical packages. The proposed biplot highlights the major aspects of the regressions by displaying the least‐squares approximation of fitted values, regression coefficients and associated t‐ratios. The utility and interpretation of the reduced‐rank regression biplot is demonstrated with an example using public health data that were previously analyzed by separate multiple regressions.
Biometrical Journal – Wiley
Published: Jan 1, 1994
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